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Sequential multiple-break procedures for nonlinear multivariate and panel models

Develop sequential sup-F-type or analogous tests and associated asymptotic theory for detecting and estimating multiple structural breaks in nonlinear multivariate regression models and nonlinear panel data models, extending beyond single-equation nonlinear least squares settings.

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Background

Sequential multiple-break procedures based on nonlinear least squares exist for single-equation models, but extensions to nonlinear multivariate and panel data models have not been developed. Establishing such procedures would broaden applicability to a wider class of macroeconomic nonlinear systems.

References

For nonlinear multivariate and panel data models, equivalent procedures are not currently available to the best of our knowledge.

— Testing for multiple change-points in macroeconometrics: an empirical guide and recent developments (2507.22204 - Boldea et al., 29 Jul 2025) in Section 6, Testing for change-points in nonlinear models (Nonlinear regression models)